GPS Solutions

, Volume 17, Issue 4, pp 475–484 | Cite as

Assessment of water vapor retrievals from a GPS receiver network

  • Stefania Bonafoni
  • Augusto Mazzoni
  • Domenico Cimini
  • Mario Montopoli
  • Nazzareno Pierdicca
  • Patrizia Basili
  • Piero Ciotti
  • Giovanni Carlesimo
Original Article


We present an assessment of a GPS receiver operational network to produce accurate integrated precipitable water vapour (IPWV) during a two-week field experiment carried out in Central Italy around the city of Rome, where different instruments were operative. This experimental activity provided an excellent opportunity to compare the GPS products with independent measurements provided by ground-based and space-based sensors and to evaluate their quality in terms of absolute accuracy of IPWV, analyzing also the spatial scale of GPS estimates. For instance, the assimilation into Numerical Weather Prediction models of IPWV provided by a GPS network or its exploitation in space geodesy applications to correct tropospheric effects requires an accuracy in the order of 0.1 cm to be ascribed to IPWV observations. In this work, we assessed that the accuracy for GPS IPWV estimates is 0.07 cm. Moreover, this experiment has pointed out strengths and limitations of an operational network for the water vapor estimation, such as a proper receiver distribution to achieve the desired spatial resolution and a coverage of GPS stations in both flat and mountains regions.


GPS network Tropospheric delay Integrated water vapor Data integration Tropospheric corrections 



This work has been carried out as part of the METAWAVE project funded by ESA/ESTEC under contract N. 21207/07/NL/HE. The author would like to thank the project team for the useful discussions and suggestions and in particular Prof. Fabio Rocca, who shared the scientific responsibility of the project, and Dr. Björn Rommen who managed the project for ESA.


  1. Askne J, Nordius H (1987) Estimation of tropospheric delay for microwaves from surface weather data. Radio Sci 22:379–386CrossRefGoogle Scholar
  2. Basili P, Bonafoni S, Ferrara R, Ciotti P, Fionda E, Ambrosini R (2001) Atmospheric water vapour retrieval by means of both a GPS network and a microwave radiometer during an experimental campaign at Cagliari (Italy) in 1999. IEEE Trans Geosci Remote Sens 39(11):2436–2443CrossRefGoogle Scholar
  3. Basili P, Bonafoni S, Mattioli V, Ciotti P, Pierdicca N (2004) Mapping the atmospheric water vapor by integrating microwave radiometer and GPS measurements. IEEE Trans Geosci Remote Sens 42(8):1657–1665CrossRefGoogle Scholar
  4. Basili P, Bonafoni S, Mattioli V, Ciotti P, Westwater ER, Fionda E (2006) Experimental campaigns for IPWV estimates in the atmosphere: comparisons between dual-channel microwave radiometers, global positioning systems and radiosondes. Riv Ital Telerilev 35:35–44Google Scholar
  5. Beutler G, Bock H, Dach R, Fridez P, Gäde A, Hugentobler U, Jäggi A, Meindl M, Mervart L, Prange L, Schaer S, Springer T, Urschl C, Walser P (2007) Bernese GPS Software Version 5.0. In: Dach R, Hugentobler U, Fridez P, Meindl M (ed). Astronomical Institute, University of Bern, BernGoogle Scholar
  6. Bevis M, Businger S, Chiswell S, Herring TA, Anthes RA, Rocken C, Ware RH (1994) GPS meteorology: mapping zenith wet delays onto precipitable water. J Appl Meteorol 33:379–386CrossRefGoogle Scholar
  7. Bonafoni S, Mattioli V, Basili P, Ciotti P, Pierdicca N (2011) Satellite-based retrieval of Precipitable Water Vapor over land by using a neural-network approach. IEEE Trans Geosci Remote Sens 49(9):3236–3248CrossRefGoogle Scholar
  8. Cimini D, Pierdicca N, Pichelli E, Ferretti R, Mattioli V, Bonafoni S, Montopoli M, Peressin D (2012) On the accuracy of integrated water vapor estimates and the potential for mitigating electromagnetic path delay error in InSAR. Atmos Meas Tech 5:1015–1030.
  9. Davis JL, Herring LTA, Shapiro II, Rogers AE, Elgered G (1985) Geodesy by radio interferometry: effects of atmospheric modelling errors on estimates of baseline length. Radio Sci 20:1593–1607CrossRefGoogle Scholar
  10. de Haan S, Holleman I, Holtslag AAM (2009) Real-Time water vapor maps from a GPS surface network: construction, validation, and applications. J Appl Meteorol Climatol 48(7):1302–1316CrossRefGoogle Scholar
  11. Desportes C, Obligis E, Eymard L (2007) On the wet tropospheric correction for altimetry in coastal regions. IEEE Trans Geosci Remote Sens 45(7):2139–2149CrossRefGoogle Scholar
  12. Duan J, Bevis M, Fang P, Bock Y, Chiswell S, Businger S, Rocken C, Solheim F, van Hove T, Ware R, McClusky S, Herring TA, King RW (1996) GPS meteorology: direct estimation of the absolute value of precipitable water. J Appl Meteorol 35:830–838CrossRefGoogle Scholar
  13. Faccani C, Ferretti R (2005) Data assimilation of high density observations: Part I. Impact on the initial conditions for the MAP/SOP IOP 2b. Q J R Meteorol Soc 131A:21–42CrossRefGoogle Scholar
  14. Ferretti R, Faccani C (2005) Data assimilation of high density observations: Part II. Impact on the forecast of the precipitation for the MAP/SOP IOP2b. Q J R Meteorol Soc 131A:43–62CrossRefGoogle Scholar
  15. Ferretti A, Prati C, Rocca F (2001) Permanent scatterers in SAR interferometry. IEEE Trans Geosci Remote Sens 39(1):8–20CrossRefGoogle Scholar
  16. Fischer J, Bennartz R (1997) Retrieval of total water vapor content from MERIS measurements. ESA reference number PO-TN-MEL-GS-005, ESA-ESTEC, Noordwijk, NetherlandsGoogle Scholar
  17. Gao BC, Kaufman Y (2003) Water vapor retrievals using Moderate Resolution Imaging Spectroradiometer (MODIS) near-infrared channels. J Geophys Res 108. doi: 10.1029/2002JD003023
  18. Han Y, Westwater ER (2000) Analysis and improvement of tipping calibration for ground-based microwave radiometers. IEEE Trans Geosci Remote Sens 38(3):1260–1276CrossRefGoogle Scholar
  19. Hanssen RF (2001) Radar interferometry: data interpretation and error analysis. Springer, New YorkGoogle Scholar
  20. Harries JE (1997) Atmospheric radiation and atmospheric humidity. Q J Royal Meteorol Soc 123(544):2173–2186CrossRefGoogle Scholar
  21. Klobuchar JA, Kunches JM (2001) Eye on the ionosphere: correction methods for GPS ionospheric range delay. GPS Solut 5(2):91–92CrossRefGoogle Scholar
  22. Kuo YH, Guo YR, Westwater ER (1993) Assimilation of precipitable water measurement into a mesoscale numerical model. Mon Weather Rev 121:1215–1238CrossRefGoogle Scholar
  23. Li Z, Muller JP, Cross P, Albert P, Fisher J, Bennartz R (2006) Assessment of the potential of MERIS near-infrared water vapor products to correct ASAR interferometric measurements. Int J Remote Sens 27(2):349–365CrossRefGoogle Scholar
  24. Liljegren JC (2000) Automatic self-calibration of ARM microwave radiometers. In: Pampaloni P, Paloscia S (eds) Microwave radiometry and remote sensing of the earth’s surface and atmosphere. VSP Press, Utrecht, pp 433–443Google Scholar
  25. Memmo A, Fionda E, Paolucci T, Cimini D, Ferretti R, Bonafoni S, Ciotti P (2005) Comparison of MM5 integrated water vapor with microwave radiometer, GPS, and radiosonde measurements. IEEE Trans Geosci Remote Sens 43(5):1050–1058CrossRefGoogle Scholar
  26. Morland J, Matzler C (2007) Spatial interpolation of GPS integrated water vapor measurements made in the Swiss Alps. Meteorol Appl 14(1):15–26CrossRefGoogle Scholar
  27. Nakamura H, Koizumi K, Mannoji N (2004) Data assimilation of GPS precipitable water vapor into the JMA mesoscale numerical weather prediction model and its impact on rainfall forecast. J Meteorol Soc Japan 82(1B):441–452CrossRefGoogle Scholar
  28. Onn F, Zebker H (2006) Correction for interferometric synthetic aperture radar atmospheric phase artifacts using time series of zenith wet delay observations from a GPS network. J Geophys Res 111(B09102). doi: 10.1029/2005JB004012
  29. Ortiz de Galisteo JP, Toledano C, Cachorro V, Torres B (2010) Improvement in PWV estimation from GPS due to the absolute calibration of antenna phase center variations. GPS Solut 14:389–395CrossRefGoogle Scholar
  30. Pacione R, Sciarretta C, Vespe F, Faccani C, Ferretti R (2001) GPS PW assimilation into MM5 with the nudging technique. Phys Chem Earth A 26:481–485CrossRefGoogle Scholar
  31. Rocca F (2007) Modeling interferogram stacks. IEEE Trans Geosci Remote Sens 45(10):3289–3299CrossRefGoogle Scholar
  32. Rocken C, Van Hove T, Johnson J, Solheim F, Ware RH, Bevis M, Chiswell S, Businger S (1995) GPS/STORM-GPS sensing of atmospheric water vapor for meteorology. J Atmos Ocean Technol 2(3):468–478CrossRefGoogle Scholar
  33. Saastamoinen J (1972) Atmospheric correction for the troposphere and stratosphere in radio ranging of satellites. In: Henriksen SW et al. (ed), The use of artificial satellites for geodesy (15), geophysics monograph series, AGU, Washington, DCGoogle Scholar
  34. Serpolla A, Bonafoni S, Biondi R, Arinò O, Basili P (2009) Validation of near infrared satellite based algorithms to retrieve atmospheric water vapour content over land. Italian J Remote Sens 41(1):37–44CrossRefGoogle Scholar
  35. Solheim FS, Vivekanandan J, Ware RH, Rocken C (1999) Propagation delays induced in GPS signals by dry air, water vapor, hydrometeors, and other particulates. J Geophys Res 104(D8):9663–9670CrossRefGoogle Scholar
  36. Trauth MH (2006) MATLAB® Recipes for Earth Sciences. Springer, HeidelbergGoogle Scholar
  37. Treuhaft RN, Lanyi GE (1987) The effect of dynamic wet troposphere on radio interferometric measurements. Radio Sci 22(22):251–265CrossRefGoogle Scholar
  38. Wackernagel H (1998) Multivariate geostatistics, 2nd edn. Springer, BerlinCrossRefGoogle Scholar
  39. Wallace JM, Hobbs PV (1977) Atmospheric Science: an Introductory Survey. Academic Press, New YorkGoogle Scholar
  40. Westwater ER (1993) Ground-based microwave remote sensing of meteorological variables. In: Janssen MA (ed) Atmospheric remote sensing by microwave radiometry. Chap 4. Wiley, New York, pp 145–213Google Scholar
  41. Wolfe DE, Gutman SI (2000) Developing an operational, surface-based, GPS, water vapor observing system for NOAA: network design and results. J Atmos Ocean Technol 17(4):426–440CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Stefania Bonafoni
    • 1
  • Augusto Mazzoni
    • 2
  • Domenico Cimini
    • 3
  • Mario Montopoli
    • 4
  • Nazzareno Pierdicca
    • 5
  • Patrizia Basili
    • 1
  • Piero Ciotti
    • 4
  • Giovanni Carlesimo
    • 4
  1. 1.Department of Electronic and Information EngineeringUniversity of PerugiaPerugiaItaly
  2. 2.Department of Civil and Environmental EngineeringSapienza University of RomeRomeItaly
  3. 3.Institute of Methodologies for the Environmental AnalysisNational Research Council (IMAA-CNR)PotenzaItaly
  4. 4.Department of Electrical and Information Engineering, DIEI and CETEMPSUniversity of L’AquilaL’AquilaItaly
  5. 5.Department of Information Engineering, Electronics and TelecommunicationsSapienza University of RomeRomeItaly

Personalised recommendations